DocumentCode :
3474932
Title :
An adaptive learning control approach
Author :
Geng, Zheng ; Jamshidi, Mo ; Carroll, Robert ; Kisner, Roger
Author_Institution :
Intelligent Automation. Inc., Rockville, MD, USA
fYear :
1991
fDate :
11-13 Dec 1991
Firstpage :
1221
Abstract :
An adaptive learning control approach is proposed which combines a mechanism to improve the control input sequence as well as to improve the learning control scheme based on the knowledge learned about the unknown system and environment. The iterative learning control problem is treated from the 2D system point of view. A 2D model for a class of iterative learning control system is formulated. A learning gain estimator algorithm based on the 2D model is presented. The overall learning control system structure is given. The proposed learning control scheme does not require prior knowledge of the controlled system and has the ability to generalize the knowledge learned from one task operation to other tasks. This scheme can be applied to nonlinear system control problems. To demonstrate the feasibility of the proposed learning algorithm, simulation results on learning control for a three-water-tank system are given. The results show an excellent learning performance, even for nonrepetitive tasks
Keywords :
adaptive control; iterative methods; learning systems; multidimensional systems; 2D system; adaptive learning control; iterative learning control; nonlinear system control; three-water-tank system; Adaptive control; Automatic control; Control system synthesis; Control systems; Error correction; Iterative algorithms; Nonlinear control systems; Nonlinear systems; Programmable control; Robotics and automation; Three-term control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
Type :
conf
DOI :
10.1109/CDC.1991.261567
Filename :
261567
Link To Document :
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